A study on the predictability of the transition day from the dry to the rainy season over South Korea

Abstract

This study was conducted to evaluate the prediction accuracies of THe Observing system Research and Predictability EXperiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) data at six operational forecast centers using the root-mean square difference (RMSD) and Brier score (BS) from April to July 2012. And it was performed to test the precipitation predictability of ensemble prediction systems (EPS) on the onset of the summer rainy season, the day of withdrawal in spring drought over South Korea on 29 June 2012 with use of the ensemble mean precipitation, ensemble probability precipitation, 10-day lag ensemble forecasts (ensemble mean and probability precipitation), and effective drought index (EDI). The RMSD analysis of atmospheric variables (geopotential-height at 500 hPa, temperature at 850 hPa, sea-level pressure and specific humidity at 850 hPa) showed that the prediction accuracies of the EPS at the Meteorological Service of Canada (CMC) and China Meteorological Administration (CMA) were poor and those at the European Center for Medium-Range Weather Forecasts (ECMWF) and Korea Meteorological Administration (KMA) were good. Also, ECMWF and KMA showed better results than other EPSs for predicting precipitation in the BS distributions. It is also evaluated that the onset of the summer rainy season could be predicted using ensemble-mean precipitation from 4-day leading time at all forecast centers. In addition, the spatial distributions of predicted precipitation of the EPS at KMA and the Met Office of the United Kingdom (UKMO) were similar to those of observed precipitation; thus, the predictability showed good performance. The precipitation probability forecasts of EPS at CMA, the National Centers for Environmental Prediction (NCEP), and UKMO (ECMWF and KMA) at 1-day lead time produced overforecasting (under-forecasting) in the reliability diagram. And all the ones at 2∼4-day lead time showed under-forecasting. Also, the precipitation on onset day of the summer rainy season could be predicted from a 4-day lead time to initial time by using the 10-day lag ensemble mean and probability forecasts. Additionally, the predictability for withdrawal day of spring drought to be ended due to precipitation on onset day of summer rainy season was evaluated using Effective Drought Index (EDI) to be calculated by ensemble mean precipitation forecasts and spreads at five EPSs.

Evaluating the Forecast Performance of the Meiyu Front Rainbelt Position: A Case Study of the 30 June to 4 July 2016 Extreme Rainfall Event

“…The 51 members of the EPS available for each forecast hour further provide a large sample size of forecasts to analyze and allows for a more robust statistical diagnosis for identifying possible dynamic and thermodynamic sources for the reduced forecast skill [9,19,20]. Uncertainty exists in the accurate predictions of weather phenomena due to a variety of factors including the initial conditions [9,21,22].…”

Synoptic Conditions and Moisture Sources for Extreme Snowfall Events Over East China

“…Due to its importance to the hydrological cycle over East China and the severity of the associated disasters, the interannual and interdecadal variations and long-term trends of the wintertime precipitation (or the wintertime extreme precipitation) have received considerable attention from the scientific community (Ao & Sun, 2016;Choi et al, 2016;Danco et al, 2016;Jia & Ge, 2017;Yuan et al, 2014;Zhai et al, 2005;Zhang et al, 2014Zhang et al, , 2015. Further, the routine forecast accuracy of the extreme snowfall events is relatively low (Byun et al, 2008;Lee et al, 2016;Lin & Wu, 2012;Yu, 2013;Zhou & Zhai, 2016). Therefore, understanding the formation mechanism for the extreme snowfall events is crucial to improve weather forecasts and mitigate negative societal impacts.…”